A kinase inhibitor lead compound and its virtual screening method and application

Abstract

The application provides a kinase inhibitor leading compound, a virtual screening method thereof and application of the kinase inhibitor leading compound in preparation of branched-chain alpha-keto acid dehydrogenase kinase inhibitors and / or drugs for treating diseases mediated by branched-chain alpha-keto acid dehydrogenase kinase. The virtual screening method provided by the application combines various virtual screening platforms to screen a large-scale compound library, improves the true positive rate of screening results, reduces the number of compounds needing experimental screening, and saves screening time and cost. In addition, the compounds I-III screened out with good binding affinity to BCKDK can be used in researches on targeting BCKDK to treat major diseases such as obesity, insulin resistance, maple syrup urine disease, neurological dysfunction, liver cancer, colorectal cancer and tumor cachexia.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of medicinal chemistry, in particular to a kinase inhibitor lead compound and a virtual screening method and application thereof. BACKGROUND

[0002] Protein kinases are important members of cell signaling pathways, which are involved in regulating various physiological functions of cells. Abnormal expression or mutation of protein kinases can lead to cancer and other diseases, and protein kinases are important drug research targets. Since imatinib was approved in 2001, 76 kinase inhibitors have been approved for marketing. Therefore, it is of great significance and broad application prospects to develop new drug leads targeting protein kinases.

[0003] With more and more protein three-dimensional structures being resolved and the rapid development of protein homology modeling methods, it is of great advantage to develop new drug leads by using virtual screening methods in computer-aided drug design with protein kinases as research targets. In recent years, with the iteration and upgrading of virtual screening methods, research teams have developed platforms for large-scale virtual screening, which has made up for the shortcomings of previous virtual screening methods with limited compound library size, such as low hit rate and high false positive rate. VirtualFlow is a large open-source virtual screening platform developed by researchers from Harvard University in 2020 and published in nature. It can effectively screen large compound libraries, but the screening platform cannot predict drugability and interactions. Therefore, we need to establish a virtual screening method combining large-scale compound library screening-ADMET property prediction-two-dimensional interaction prediction to improve the speed and quality of lead compounds and drugability.

[0004] The branched-chain amino acid (BCAA) catabolic pathway plays a key role in the maintenance of BCAA homeostasis in mammals. Branched-chain alpha-keto acid dehydrogenase kinase (BCKDK) in mitochondria is a key negative regulatory kinase in the BCAA catabolic pathway, which can phosphorylate the alpha subunit of branched-chain alpha-keto acid dehydrogenase (BCKDHA or E1a) to inactivate it, and is closely related to various major diseases in humans.

[0005] Studies have shown a strong link between elevated plasma branched-chain amino acids and insulin resistance (IR). Accumulation of BCAAs and branched-chain α-keto acids (BCKAs) has been found in genetically obese mice. Pharmacological inhibition of BCAA catabolism by BCKDK inhibitors restores BCAA catabolism flux, reduces BCAA / BCKA abundance in genetically obese mice, and significantly decreases IR, confirming that small-molecule BCKDK inhibitors have a significant ameliorative effect on IR in high-fat diet-induced obese mice. Other studies have shown that maple syrup diabetes (MSUD) is an autosomal recessive disease caused by BCKDC deficiency. In individuals with MSUD, BCAA oxidation is inhibited, leading to the accumulation of BCAAs and BCKAs, impairing neuronal function and brain energy metabolism, resulting in symptoms such as neurological dysfunction and epilepsy. These studies provide a basis for research into targeted BCKDK therapy for obesity, IR, and maple syrup diabetes.

[0006] Furthermore, branched-chain amino acid (BCAA) catabolism disorders are prevalent in various tumors. In hepatocellular carcinoma (HCC), BCAA catabolism disorders lead to BCAA accumulation, thereby activating mTORC1 and its downstream effector proteins, and promoting tumor development and progression. Low-dose dietary intake of the branched-chain α-keto acid dehydrogenase kinase (BCKDK) inhibitor 3,6-dichloro-2-benzothiophene carboxylic acid (BT2) effectively reduced tumor growth in experimental mice, indicating that enhancing BCAA catabolism can effectively inhibit the growth of HCC cells. BCKDK also promotes colorectal cancer development by activating the MEK-ERK signaling pathway. Studies have found that BCKDK can promote JB6C141 cell transformation and the growth of rectal cancer cells, and the expression level of BCKDK is significantly increased in colorectal cancer tissues, negatively correlated with the survival of colorectal cancer patients. Further research shows that BCKDK is a direct upstream kinase of MEK, promoting colorectal cancer development by phosphorylating MEK and activating the MAPK signaling pathway. Phenylbutyrate (PB), a known BCKDK inhibitor, can inhibit the growth-promoting effect of BCKDK on colorectal cancer and its catalytic activity against MEK1. However, PB is also an inhibitor of histidine deacetyltransferase, not specific to BCKDK, and its inhibition of BCKDK requires very high concentrations. Furthermore, significant dose-dependent neurotoxicity was observed in phase I clinical trials. Therefore, the discovery of specific lead compounds targeting BCKDK is of great value for treating colorectal cancer caused by persistent MEK activation and its associated drug resistance.

[0007] Numerous studies have also shown that metabolic disorders occur in patients with advanced cancer. Abnormally enhanced branched-chain amino acid (BCAA) metabolism and altered metabolic enzyme activity lead to insufficient anabolism and enhanced catabolism, resulting in cachexia and poor prognosis in patients with intermediate and advanced cancer. Cancer cachexia is a common outcome of deteriorating nutritional status in cancer patients. methyl butyrate, rich in BCAAs and their intermediate metabolites, is used for nutritional support and the treatment of cancer cachexia in cancer patients. However, due to anabolistic feedback and insulin resistance, simply supplementing with BCAAs is insufficient to alleviate excessive catabolism in cancer patients. The development of the BCKDK lead compound can improve the efficacy of nutritional support therapy by alleviating insulin resistance and disrupting the BCAA anabolistic metabolic cycle, providing new ideas and methods for the development of drugs to prevent and treat cancer cachexia.

[0008] In conclusion, drugs targeting BCKDK have significant value and promising applications in the prevention and treatment of major diseases such as obesity, insulin resistance, maple syrup diabetes, neurological dysfunction, liver cancer, colorectal cancer, and tumor cachexia. Summary of the Invention

[0009] To overcome the deficiencies in the prior art, this invention provides a virtual screening method for kinase inhibitor lead compounds, and provides the structure of the compounds obtained by screening using this method, as well as the application of the compounds as BCKDK inhibitors and / or drugs with the compounds as the main active ingredients in the treatment of major diseases such as obesity, insulin resistance, maple syrup diabetes, neurological dysfunction, liver cancer, colorectal cancer, and tumor cachexia by targeting BCKDK.

[0010] To achieve the above objectives, the present invention adopts the following technical solution:

[0011] A first aspect of the present invention is to provide a virtual screening method for kinase inhibitor lead compounds, comprising the following steps:

[0012] (1) Obtain the three-dimensional structure of protein kinase from the Protein Data Bank;

[0013] (2) Determine the location information, spatial size, and key amino acid residues of the compound binding site;

[0014] (3) Determine the ligand compound library to be used;

[0015] (4) Using the target protein kinase as the target, rigid docking is performed on the binding site of the compound at the target using a molecular docking program. Based on the rigid docking scoring results, a certain number of top-ranked compounds are selected as initial screening data and then flexible docking is performed. Based on the flexible docking scoring results, a certain number of top-ranked compounds are selected as a fine screening database.

[0016] (5) Predict the ADMET properties and two-dimensional interaction modes of compounds in the fine screening database, and screen out compounds with good ADMET properties, no unreliable interactions, and containing both hydrophobic interactions and hydrogen bonding interactions, with dissimilar structures and easy to purchase as lead compounds.

[0017] (6) Further evaluate the bioactivity of the above-mentioned lead compounds and screen for compounds with good binding affinity and bioactivity as inhibitors of the target protein kinase.

[0018] Furthermore, the ligand compound library used in step (3) is selected from the Enamine ligand library provided by the VirtualFlow large-scale compound library screening platform.

[0019] Furthermore, the molecular docking platform mentioned in step (4) is the VirtualFlow large-scale compound library screening platform. Rigid docking uses the qvina02 and smina_rigid programs of this platform; flexible docking uses the vina program of this platform.

[0020] Furthermore, in step (6), the bioactivity of the candidate compounds is evaluated using surface plasmon resonance, Western blotting, and cell proliferation activity assays.

[0021] Furthermore, the above-mentioned surface plasmon resonance experiment used an NTA sensor chip.

[0022] A second aspect of the present invention is to provide compounds screened by the above-described virtual screening method, selected from compounds I, II, and III having the structures shown in Formula I, Formula II, and Formula III:

[0023]

[0024] A third aspect of the present invention is to provide the use of the above-mentioned compounds in the preparation of branched-chain α-keto acid dehydrogenase kinase inhibitors, which include compounds I, II, III or derivatives thereof, or pharmaceutically acceptable salts, esters or solvates thereof.

[0025] Furthermore, the general structural formulas of the derivatives of compounds I, II, and III are Formula IV, Formula V, and Formula VI, respectively; wherein R1, R2, and R3 are each independently selected from H, C1-10 alkyl, C2-10 alkenyl, C2-10 alkynyl, C3-10 cycloalkyl, C1-10 substituted alkyl, C2-10 substituted alkenyl, C3-10 substituted cycloalkyl, C3-10 substituted cycloalkenyl, and C1-10 ether, wherein the substituents are selected from nitro, amino, carboxyl, halogen atom, hydroxyl, mercapto, C1-6 alkylthio, C1-6 alkoxy, ester, C1-6 alkoxycarbonyl, C1- The aryl group is selected from one or more of the following groups: 6-alkyloxy, amide, aminocarbonyl, C1-6 alkylaminocarbonyl, di(C1-6 alkyl)aminocarbonyl, optionally substituted aryl, optionally substituted heteroaryl, optionally substituted arylC1-6 alkyl, optionally substituted heteroarylC1-6 alkyl, optionally substituted aryloxy, optionally substituted heteroaryloxy, optionally substituted arylC1-6 alkyloxy, optionally substituted heteroarylC1-6 alkyloxy, and optionally substituted heteroarylC1-6 alkyloxy, wherein the substituent on the aryl or heteroaryl group is selected from one or more of the following groups: hydroxyl, mercapto, amino, nitro, halogen atom, C1-6 alkyl, C1-6 alkoxy, C1-6 alkylthio, and carboxyl.

[0026]

[0027] A fourth aspect of the present invention is to provide a branched-chain α-keto acid dehydrogenase kinase inhibitor, which comprises the above-described compound or its derivatives, or pharmaceutically acceptable salts, esters, or solvates thereof.

[0028] Furthermore, the general structural formulas of the derivatives of compounds I, II, and III are Formula IV, Formula V, and Formula VI, respectively; wherein R1, R2, and R3 are each independently selected from H, C1-10 alkyl, C2-10 alkenyl, C2-10 alkynyl, C3-10 cycloalkyl, C1-10 substituted alkyl, C2-10 substituted alkenyl, C3-10 substituted cycloalkyl, C3-10 substituted cycloalkenyl, and C1-10 ether, wherein the substituents are selected from nitro, amino, carboxyl, halogen atom, hydroxyl, mercapto, C1-6 alkylthio, C1-6 alkoxy, ester, C1-6 alkoxycarbonyl, C1- The aryl group is selected from one or more of the following groups: 6-alkyloxy, amide, aminocarbonyl, C1-6 alkylaminocarbonyl, di(C1-6 alkyl)aminocarbonyl, optionally substituted aryl, optionally substituted heteroaryl, optionally substituted arylC1-6 alkyl, optionally substituted heteroarylC1-6 alkyl, optionally substituted aryloxy, optionally substituted heteroaryloxy, optionally substituted arylC1-6 alkyloxy, optionally substituted heteroarylC1-6 alkyloxy, and optionally substituted heteroarylC1-6 alkyloxy, wherein the substituent on the aryl or heteroaryl group is selected from one or more of the following groups: hydroxyl, mercapto, amino, nitro, halogen atom, C1-6 alkyl, C1-6 alkoxy, C1-6 alkylthio, and carboxyl.

[0029]

[0030] A fifth aspect of the invention is to provide the use of the above-described compounds or branched-chain α-keto acid dehydrogenase kinase inhibitors in the preparation of a medicament for treating diseases mediated by branched-chain α-keto acid dehydrogenase kinase, the medicament comprising compounds I, II, III or derivatives thereof, or pharmaceutically acceptable salts, esters or solvates thereof.

[0031] Furthermore, the general structural formulas of the derivatives of compounds I, II, and III are Formula IV, Formula V, and Formula VI, respectively; wherein R1, R2, and R3 are each independently selected from H, C1-10 alkyl, C2-10 alkenyl, C2-10 alkynyl, C3-10 cycloalkyl, C1-10 substituted alkyl, C2-10 substituted alkenyl, C3-10 substituted cycloalkyl, C3-10 substituted cycloalkenyl, and C1-10 ether, wherein the substituents are selected from nitro, amino, carboxyl, halogen atom, hydroxyl, mercapto, C1-6 alkylthio, C1-6 alkoxy, ester, C1-6 alkoxycarbonyl, C1- The aryl group is selected from one or more of the following groups: 6-alkyloxy, amide, aminocarbonyl, C1-6 alkylaminocarbonyl, di(C1-6 alkyl)aminocarbonyl, optionally substituted aryl, optionally substituted heteroaryl, optionally substituted arylC1-6 alkyl, optionally substituted heteroarylC1-6 alkyl, optionally substituted aryloxy, optionally substituted heteroaryloxy, optionally substituted arylC1-6 alkyloxy, optionally substituted heteroarylC1-6 alkyloxy, and optionally substituted heteroarylC1-6 alkyloxy, wherein the substituent on the aryl or heteroaryl group is selected from one or more of the following groups: hydroxyl, mercapto, amino, nitro, halogen atom, C1-6 alkyl, C1-6 alkoxy, C1-6 alkylthio, and carboxyl.

[0032]

[0033] Furthermore, the aforementioned diseases are selected from at least one of the following: obesity, insulin resistance, maple syrup diabetes, neurological dysfunction, liver cancer, colorectal cancer, and tumor cachexia.

[0034] The present invention adopts the above technical solution and has the following technical effects compared with the prior art:

[0035] The virtual screening method provided by this invention combines multiple virtual screening platforms to screen large-scale compound libraries, improving the true positive rate of screening results, reducing the number of compounds requiring experimental screening, and saving screening time and costs. Furthermore, the screened compounds I-III, which have good binding affinity to BCKDK, can be used in research on BCKDK-targeted therapy for major diseases such as obesity, insulin resistance, maple syrup diabetes, neurological dysfunction, liver cancer, colorectal cancer, and tumor cachexia. Attached Figure Description

[0036] Figure 1 This is a virtual screening flowchart for kinase inhibitor lead compounds;

[0037] Figure 2 The BCKDK allosteric site selected for this description;

[0038] Figure 3 The results show the affinity analysis of compounds I-III with the surface plasmon resonance of BCKDK protein;

[0039] Figure 4 The inhibitory effects of various compounds on BCKDK phosphorylation downstream protein (BCKDHA) at a concentration of 40 μM were demonstrated.

[0040] Figure 5 For analysis using Image Lab software Figure 4 Statistical results after optical density analysis of each lane band;

[0041] Figure 6 The inhibition rates of various compounds on the proliferation of human 293T cells at different concentrations were shown. Detailed Implementation

[0042] This invention provides a kinase inhibitor lead compound, its virtual screening method, and its application. The kinase inhibitor lead compound is a compound having the structure shown in Formula I, Formula II, or Formula III, or its derivatives, or pharmaceutically acceptable salts, esters, or solvates thereof.

[0043]

[0044] The present invention will now be described in detail with reference to specific embodiments and accompanying drawings to enable a better understanding of the invention. However, the following embodiments do not limit the scope of the invention.

[0045] Unless otherwise specified, the methods used in the embodiments are conventional methods, and the reagents used are commercially available reagents or reagents prepared according to conventional methods, unless otherwise specified.

[0046] Example 1

[0047] like Figure 1 This embodiment provides a virtual screening method for kinase inhibitor lead compounds, the specific steps of which are as follows:

[0048] I. Virtual Filtering

[0049] (1) Obtaining the three-dimensional crystal structure of the protein and determining the location information of the ligand binding site: The three-dimensional crystal structure of BCKDK was obtained from the Protein Databank (search number: 3TZ0); the downloaded protein structure was opened with Discovery Studio software to remove water molecules and redundant ligands in the structure. Then, the Prepare Protein module in the software was used to preprocess the protein structure to remove protein polymorphisms and supplement incomplete amino acid residues; the protein was defined as a receptor molecule, and the From Receptor Cavities function module was used to find the ligand binding site, and then the ligand binding site was retained. Figure 2The allosteric site shown is used to delete other active sites. The coordinates of this site are recorded as follows: X = 5.94, Y = -26.30, Z = 17.21, radius = 11.2. The results are recorded in the docking parameter file config.txt. The processed protein structure is saved in .pdb format.

[0050] (2) Preparation of docking acceptor files: Open the protein pdb file processed in step (1) with AutoDockTools software, and then perform operations such as hydrogenation, Gasteiger charge calculation, and atom specification AD4 type on the protein, and then save it as receptor.pdbqt; prepare rigid.pdbqt and flexible.pdbqt files according to the process of Flexible Receptor PDBQT Files – the “FlexibleResidues” Menu in AutoDock4.2.6_UserGuide (here, the flexible residues are specified as: LEU40,THR41,PRO42,LEU46,LEU168,GLY169,MET172,ILE190,ILE235,PRO236,MET237,PRO238,TYR346,ALA347,TYR349,LEU350,GLY351,LEU370,ARG371,ILE373)

[0051] (3) Preparation of ligand files: Go to the VirtualFlow website (https: / / virtual-flow.org / ) and enter the REAL Library interface under Download. Set the filter criteria as follows: MW: 200-4000; Partition Coefficient (SlogP): 2-3; Topological Polar Surface Area (TPSA): 20 to 120; Hydrogen Bond Acceptors (HBA): 2-5; Hydrogen Bond Donors (HBD): 1-5; Rotatable Bonds (RotB): 1-3. The results show that 11.5 million molecules were selected as ligand libraries. Download the tranches.sh and collections.txt files of this ligand library.

[0052] (4) Rigid docking: Use VirtualFlow for rigid docking. First, download and decompress VFVS-develop (URL: http: / / github.com / VirtualFlow / VFVS / archive / develop.tar.gz); then put the receptor.pdbqt file in step (2) into the VFVS-develop / input-files / receptor / directory, and put the tranches.sh file and collections.txt file in step (3) into the VFVS-develop / input-files / ligand-library / directory and execute the source tranches.sh command to download the ligand library files to this directory; then set the running parameters through the all.ctrl and template1.slurm.sh files in the tools / templates / directory (here, the docking programs are selected as qvina02 and smina_rigid), copy the collections.txt in step (3) as the todo.all file in this directory; finally, perform docking task preparation and docking task submission through the. / vf_prepare_folders.sh and. / vf_start_jobline.sh programs. After docking, each of the qvina02 and smina_rigid programs screens and scores the top 25,000 molecules, and after removing duplicates, 47,702 small molecules are obtained to form a primary screening database for subsequent flexible docking.

[0053] (5) Flexible docking: The flexible docking process is the same as the rigid docking process in step (4), except that the receptor files need to be modified to rigid.pdbqt and flexible.pdbqt in step (2), the ligand library is modified to the primary screening database in step (4), and the docking program is selected as vina. After flexible docking, screen and score the top 200 small molecules to form a refined screening database.

[0054] (6) Prediction of ADMET properties and two-dimensional interaction modes: Use Hermite software to predict the ADMET properties of the refined screening compounds obtained in step (5), exclude compounds with 5 < LogD7.4 < 1, 3 < LogP < 0, and LD50 (mg / kg) < 500, and obtain 71 compounds; then use Discovery studio to predict the two-dimensional interaction modes between these 71 compounds and the BCKDK protein, and retain compounds that do not have untrustworthy interactions and contain both hydrophobic interactions and hydrogen bond interactions at the same time, and obtain 22 compounds;

[0055] (7) Observe the structural formulas of the 22 compounds in step (6). If more than two compounds have similar structures, only one is retained. Considering the ease of purchasing the compounds, seven compounds are finally purchased as lead compounds.

[0056] II. Bioactivity Screening

[0057] The binding affinity between seven seed compounds and His-tagged BCKDK was evaluated using surface plasmon resonance (SPR) technology. A Biacore T200 instrument and an NTA sensor chip were used. Before the experiment, ligand pre-enrichment and regeneration conditions were selected. The NTA sensor chip was placed in the chip chamber, and HBS-P was selected as the experimental buffer. First, surface conditions were adapted in channels F1 and F2 using 350 mM EDTA solution as the regeneration solution, with a flow rate of 10 μL / min and a temperature of 25 °C for 1 minute. After the system stabilized, a stable baseline was output. Then, 0.5 mM nickel chloride solution was injected into channel F2, with a flow rate of 10 μL / min and a temperature of 25 °C for 1 minute. Next, His-tagged BCKDK protein at a concentration of 10 μg / ml was captured in channel F2, with a flow rate of 10 μL / min and a temperature of 25 °C for 3 minutes. Small molecule compounds were dissolved in 1×PBS-P + 2% DMSO buffer to prepare test solutions with concentrations of 50 μM, 25 μM, 12.5 μM, 6.25 μM, 3.125 μM, 1.5625 μM, and 0.78125 μM. The solutions were flowed through the chip surface at a flow rate of 30 μL / min, and the binding and dissociation of the small molecules with BCKDK were recorded. Channel F1 was the control channel, and channel F2 was the experimental channel. After dissociation, a 350 mM EDTA solution was used as a regeneration solution to elute the small molecule compounds remaining on the NTA chip, releasing the binding sites of the receptor protein. After the test, the equilibrium dissociation constant KD was analyzed using the "Affinity" model in Biacore T200 evaluation software version 2.0.

[0058] The results are as follows Figure 3 As shown in Table 1 below, compounds I, II, and III (drug-like compounds screened from the Enamine database, with Enamine IDs Z4742618028, Z1504177490, and Z4742621925, respectively) exhibit good binding affinity for BCKDK, with dissociation equilibrium constants (KD) of 12.99 μM, 3.90 μM, and 1.86 μM, respectively.

[0059] Table 1. Molecular weights and dissociation equilibrium constants K of compounds I-III D

[0060]

[0061] Example 2

[0062] This embodiment verifies the performance of compounds I to III. The specific experimental steps and results are as follows:

[0063] 1. Western Blotting

[0064] Western blotting was used to investigate the inhibitory activity of compounds I-III on the protein BCKDK in human 293T cells compared to the positive control compound BT2, expressed as the degree of phosphorylation of their substrate E1α. Human embryonic kidney 293T cells cultured to the logarithmic growth phase were seeded in six-well plates at 2 × 10⁶ cells per well. 5 Cells were cultured at 37°C and 5% CO2 for 12-24 hours until cell adhesion. The old culture medium was discarded, and 1.5 ml of complete culture medium containing 40 μM of the compound was added to each well. Two replicates were set up for each compound, along with a solvent control group (DMSO added but no compound) and a blank control group (no DMSO added and no compound added). Cells were cultured at 37°C and 5% CO2 for 48 hours. Cells were then collected in 1.5 ml EP tubes and counted using a hemocytometer. The results are shown in Table 2 below. After counting, the cells were centrifuged at 800 rpm for 3 minutes, the supernatant was discarded, and the cells were washed once with 1×PBS. Based on the cell count results, 50-150 μl of lysis buffer (with appropriate amounts of protease inhibitor and phosphatase inhibitor added beforehand) was added to each cell pellet. After mixing, the pellet was placed on ice for 20 minutes, centrifuged at 12000g for 5 minutes, and the supernatant was collected into a new EP tube as the total protein solution for each sample. Protein concentration was determined for each sample using a BCA protein quantification kit. Based on the results, the samples were diluted to the same concentration using lysis buffer. 15-20 μl of each sample was subjected to SDS-PAGE electrophoresis. The electrophoresis, transfer, primary antibody incubation, and secondary antibody incubation procedure were as follows: Electrophoresis at 145V for 1.5 h; then transfer at 110V for 1 h; washing with 1×TBST for 5 min × 3 times; blocking with 1×TBST containing 5% skim milk powder at room temperature for 1 h; overnight incubation with primary antibody at 4°C (antibodies: pE1α-antibody, E1α-antibody, and internal control β-actin); washing with 1×TBST for 10 min × 3 times; incubation with secondary antibody containing horseradish peroxidase at room temperature for 1.5 h; washing with 1×TBST for 10 min × 3 times, followed by development. Immunoblotting images are shown below. Figure 4 As shown, the optical density of the strips was analyzed using Image Lab software, the area under the optical density curve was calculated, and the statistical results were obtained using GraphPad Prism software. Figure 5 As shown.

[0065] Table 2. Cell count results of human 293T cells after 48 h of treatment with 40 μM compounds in 6-well plates.

[0066]

[0067] The results showed that in 293T cells treated with compounds II and III, the phosphorylation level of E1α was reduced, significantly lower than that of the positive control compound BT2. This indicates that compounds II and III are more effective BCKDK inhibitors than the positive control compound BT2.

[0068] 2. Cell proliferation activity test

[0069] The inhibitory effects of compounds I–III and the positive control compound BT2 on the proliferation of human 293T cells at concentrations of 0.05 μM, 0.25 μM, 0.5 μM, 2.5 μM, 5 μM, 25 μM, 50 μM, 250 μM, and 500 μM were detected using a cell counting kit 8 (CCK-8). Human 293T cells in the logarithmic growth phase were prepared to a concentration of 2 × 10⁻⁶ cells / cells. 4 Cell suspension was prepared at 1 / ml, and then 200 μl was seeded into each well of a 96-well plate. The cells were incubated for 24 h in a 5% CO2, 37°C incubator until adherence. The compound was prepared into solutions of different concentrations. Adherent cells were removed, and after discarding the waste culture medium, 100 μl of complete culture medium containing different concentrations of the compound was added to each well. Three replicates were set up for each concentration of each compound, along with blank and negative controls. After incubation for 48 h, 10 μl of CCK-8 reagent was added, and after incubation for 2 h, the absorbance (OD value) at 450 nm was measured using a microplate reader. The cell proliferation inhibition rate (%) was calculated using the formula: [1 - (OD value)] 不同浓度化合物 -OD 空白对照 ) / (OD 阴性对照 -OD 空白对照 The inhibition rate was calculated using 100, and nonlinear fitting curves were generated using GraphPad Prism software. The IC50 of each compound was also calculated. 50 Value, result as Figure 6 As shown.

[0070] IC50 of compounds I-III and positive control compound BT2 50 The values ​​were 10.17 μM, 10.17 μM, 15.6 μM, and >200 μM, respectively. Combined with the cell count results recorded in Table 2 after treating human 293T cells with each compound at 40 μM in 6-well plates for 48 h, the results showed that compounds I–III significantly inhibited the proliferation of human 293T cells.

[0071] The specific embodiments of the present invention have been described in detail above, but they are only examples, and the present invention is not limited to the specific embodiments described above. For those skilled in the art, any equivalent modifications and substitutions to the present invention are also within the scope of the present invention. Therefore, all equivalent changes and modifications made without departing from the spirit and scope of the present invention should be covered within the scope of the present invention.

Claims

1. The use of compound I having the structure shown in Formula I or a pharmaceutically acceptable salt thereof in the preparation of branched-chain α-keto acid dehydrogenase kinase inhibitors. ； Formula I.

2. The use of compound II having the structure shown in Formula II or a pharmaceutically acceptable salt thereof in the preparation of branched-chain α-keto acid dehydrogenase kinase inhibitors. ； Formula II.

3. The use of compound III having the structure shown in Formula III or a pharmaceutically acceptable salt thereof in the preparation of branched-chain α-keto acid dehydrogenase kinase inhibitors. ； Formula III.

4. The use of compound I having the structure shown in Formula I or a pharmaceutically acceptable salt thereof in the preparation of medicaments for treating diseases mediated by branched-chain α-keto acid dehydrogenase kinase. ； Formula I.

5. The use of compound II having the structure shown in Formula II or a pharmaceutically acceptable salt thereof in the preparation of medicaments for treating diseases mediated by branched-chain α-keto acid dehydrogenase kinase. ； Formula II.

6. Use of compound III having the structure shown in Formula III or a pharmaceutically acceptable salt thereof in the preparation of medicaments for treating diseases mediated by branched-chain α-keto acid dehydrogenase kinase. ； Formula III.

7. The application according to any one of claims 4-6, characterized in that, The disease is selected from at least one of the following: obesity, insulin resistance, maple syrup diabetes, neurological dysfunction, liver cancer, colorectal cancer, and tumor cachexia.

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